Handheld electronic device and method for dual-mode disambiguation of text input

ABSTRACT

A handheld electronic device includes a reduced QWERTY keyboard and is enabled with disambiguation software that is operable to disambiguate text input. In response to an ambiguous editing input at a location preceding at least a portion of an output word, the software performs one disambiguation operation with respect to the editing input and another disambiguation operation with respect to the editing input in combination with the at least portion of the output word. The results are output in order of decreasing frequency value, with the results of the one disambiguation operation having the portion of the output word appended thereto.

CROSS-REFERENCE TO RELATED APPLICATION

The instant application is a continuation application of U.S. patentapplication Ser. No. 12/346,116 filed Dec. 30, 2008 now U.S. Pat. No.7,843,364, which is a continuation application of U.S. patentapplication Ser. No. 11/427,946 filed Jun. 30, 2006, now U.S. Pat. No.7,586,423, the disclosures of which application and patent areincorporated herein by reference.

BACKGROUND

1. Field

The disclosed and claimed concept relates generally to handheldelectronic devices and, more particularly, to a handheld electronicdevice having a reduced keyboard and a text input disambiguationfunction that can perform dual-mode disambiguation in response to anediting input.

2. Background Information

Numerous types of handheld electronic devices are known. Examples ofsuch handheld electronic devices include, for instance, personal dataassistants (PDAs), handheld computers, two-way pagers, cellulartelephones, and the like. Many handheld electronic devices also featurewireless communication capability, although many such handheldelectronic devices are stand-alone devices that are functional withoutcommunication with other devices.

Such handheld electronic devices are generally intended to be portable,and thus are of a relatively compact configuration in which keys andother input structures often perform multiple functions under certaincircumstances or may otherwise have multiple aspects or featuresassigned thereto. With advances in technology, handheld electronicdevices are built to have progressively smaller form factors yet haveprogressively greater numbers of applications and features residentthereon. As a practical matter, the keys of a keypad can only be reducedto a certain small size before the keys become relatively unusable. Inorder to enable text entry, however, a keypad must be capable ofentering all twenty-six letters of the Latin alphabet, for instance, aswell as appropriate punctuation and other symbols.

One way of providing numerous letters in a small space has been toprovide a “reduced keyboard” in which multiple letters, symbols, and/ordigits, and the like, are assigned to any given key. For example, atouch-tone telephone includes a reduced keypad by providing twelve keys,of which ten have digits thereon, and of these ten keys eight have Latinletters assigned thereto. For instance, one of the keys includes thedigit “2” as well as the letters “A”, “B”, and “C”. Other known reducedkeyboards have included other arrangements of keys, letters, symbols,digits, and the like. Since a single actuation of such a key potentiallycould be intended by the user to refer to any of the letters “A”, “B”,and “C”, and potentially could also be intended to refer to the digit“2”, the input generally is an ambiguous input and is in need of sometype of disambiguation in order to be useful for text entry purposes.

In order to enable a user to make use of the multiple letters, digits,and the like on any given key, numerous keystroke interpretation systemshave been provided. For instance, a “multi-tap” system allows a user tosubstantially unambiguously specify a particular character on a key bypressing the same key a number of times equivalent to the position ofthe desired character on the key. Another exemplary keystrokeinterpretation system would include key chording, of which various typesexist. For instance, a particular character can be entered by pressingtwo keys in succession or by pressing and holding a first key whilepressing a second key. Still another exemplary keystroke interpretationsystem would be a “press-and-hold/press-and-release” interpretationfunction in which a given key provides a first result if the key ispressed and immediately released, and provides a second result if thekey is pressed and held for a short period of time. Another keystrokeinterpretation system that has been employed is a software-based textdisambiguation function. In such a system, a user typically presses keysto which one or more characters have been assigned, generally pressingeach key one time for each desired letter, and the disambiguationsoftware attempts to predict the intended input. Numerous such systemshave been proposed, and while many have been generally effective fortheir intended purposes, shortcomings still exist.

It would be desirable to provide an improved handheld electronic devicewith a reduced keyboard that seeks to mimic a QWERTY keyboard experienceor other particular keyboard experience. Such an improved handheldelectronic device might also desirably be configured with enoughfeatures to enable text entry and other tasks with relative ease.

BRIEF DESCRIPTION OF THE DRAWINGS

A full understanding of the disclosed and claimed concept can be gainedfrom the following Description when read in conjunction with theaccompanying drawings in which:

FIG. 1 is a top plan view of an improved handheld electronic device inaccordance with the disclosed and claimed concept;

FIG. 2 is a schematic depiction of the improved handheld electronicdevice of FIG. 1;

FIG. 2A is a schematic depiction of a portion of the handheld electronicdevice of FIG. 2;

FIGS. 3A, 3B, and 3C are an exemplary flowchart depicting certainaspects of a disambiguation function that can be executed on thehandheld electronic device of FIG. 1;

FIG. 4 is another exemplary flowchart depicting certain aspects of alearning method that can be executed on the handheld electronic device;

FIG. 5 is an exemplary output during a text entry operation;

FIG. 6 is another exemplary output during another part of the text entryoperation;

FIG. 7 is another exemplary output during another part of the text entryoperation;

FIG. 8 is another exemplary output during another part of the text entryoperation;

FIG. 9 is an exemplary output during another text entry operation; and

FIG. 10 is another exemplary output during another part of the othertext entry operation.

Similar numerals refer to similar parts throughout the specification.

DESCRIPTION

An improved handheld electronic device 4 is indicated generally in FIG.1 and is depicted schematically in FIG. 2. The exemplary handheldelectronic device 4 includes a housing 6 upon which is disposed aprocessor unit that includes an input apparatus 8, an output apparatus12, a processor 16, a memory 20, and at least a first routine. Theprocessor 16 may be, for instance, and without limitation, amicroprocessor (μP) and is responsive to inputs from the input apparatus8 and provides output signals to the output apparatus 12. The processor16 also interfaces with the memory 20. The processor 16 and the memory20 together form a processor apparatus. Examples of handheld electronicdevices are included in U.S. Pat. Nos. 6,452,588 and 6,489,950, whichare incorporated by record herein.

As can be understood from FIG. 1, the input apparatus 8 includes akeypad 24 and a thumbwheel 32. As will be described in greater detailbelow, the keypad 24 is in the exemplary form of a reduced QWERTYkeyboard including a plurality of keys 28 that serve as input members.It is noted, however, that the keypad 24 may be of other configurations,such as an AZERTY keyboard, a QWERTZ keyboard, or other keyboardarrangement, whether presently known or unknown, and either reduced ornot reduced. As employed herein, the expression “reduced” and variationsthereof in the context of a keyboard, a keypad, or other arrangement ofinput members, shall refer broadly to an arrangement in which at leastone of the input members has assigned thereto a plurality of linguisticelements such as, for example, characters in the set of Latin letters,whereby an actuation of the at least one of the input members, withoutanother input in combination therewith, is an ambiguous input since itcould refer to more than one of the plurality of linguistic elementsassigned thereto. As employed herein, the expression “linguisticelement” and variations thereof shall refer broadly to any element thatitself can be a language object or from which a language object can beconstructed, identified, or otherwise obtained, and thus would include,for example and without limitation, characters, letters, strokes,ideograms, phonemes, morphemes, digits, and the like. As employedherein, the expression “language object” and variations thereof shallrefer broadly to any type of object that may be constructed, identified,or otherwise obtained from one or more linguistic elements, that can beused alone or in combination to generate text, and that would include,for example and without limitation, words, shortcuts, symbols,ideograms, and the like.

The system architecture of the handheld electronic device 4advantageously is organized to be operable independent of the specificlayout of the keypad 24. Accordingly, the system architecture of thehandheld electronic device 4 can be employed in conjunction withvirtually any keypad layout substantially without requiring anymeaningful change in the system architecture. It is further noted thatcertain of the features set forth herein are usable on either or both ofa reduced keyboard and a non-reduced keyboard.

The keys 28 are disposed on a front face of the housing 6, and thethumbwheel 32 is disposed at a side of the housing 6. The thumbwheel 32can serve as another input member and is both rotatable, as is indicatedby the arrow 34, to provide selection inputs to the processor 16, andalso can be pressed in a direction generally toward the housing 6, as isindicated by the arrow 38, to provide another selection input to theprocessor 16.

As can further be seen in FIG. 1, many of the keys 28 include a numberof linguistic elements 48 disposed thereon. As employed herein, theexpression “a number of” and variations thereof shall refer broadly toany quantity, including a quantity of one. In the exemplary depiction ofthe keypad 24, many of the keys 28 include two linguistic elements, suchas including a first linguistic element 52 and a second linguisticelement 56 assigned thereto.

One of the keys 28 of the keypad 24 includes as the characters 48thereof the letters “Q” and “W”, and an adjacent key 28 includes as thecharacters 48 thereof the letters “E” and “R”. It can be seen that thearrangement of the characters 48 on the keys 28 of the keypad 24 isgenerally of a QWERTY arrangement, albeit with many of the keys 28including two of the characters 48.

The output apparatus 12 includes a display 60 upon which can be providedan output 64. An exemplary output 64 is depicted on the display 60 inFIG. 1. The output 64 includes a text component 68 and a variantcomponent 72. The variant component 72 includes a default portion 76 anda variant portion 80. The display also includes a caret 84 that depictsgenerally where the next input from the input apparatus 8 will bereceived.

The text component 68 of the output 64 provides a depiction of thedefault portion 76 of the output 64 at a location on the display 60where the text is being input. The variant component 72 is disposedgenerally in the vicinity of the text component 68 and provides, inaddition to the default proposed output 76, a depiction of the variousalternate text choices, i.e., alternates to the default proposed output76, that are proposed by an input disambiguation function in response toan input sequence of key actuations of the keys 28.

As will be described in greater detail below, the default portion 76 isproposed by the disambiguation function as being the most likelydisambiguated interpretation of the ambiguous input provided by theuser. The variant portion 80 includes a predetermined quantity ofalternate proposed interpretations of the same ambiguous input fromwhich the user can select, if desired. It is noted that the exemplaryvariant portion 80 is depicted herein as extending vertically below thedefault portion 76, but it is understood that numerous otherarrangements could be provided.

The memory 20 is depicted schematically in FIG. 2A. The memory 20 can beany of a variety of types of internal and/or external storage media suchas, without limitation, RAM, ROM, EPROM(s), EEPROM(s), the like thatprovide a storage register for data storage such as in the fashion of aninternal storage area of a computer, and can be volatile memory ornonvolatile memory. The memory 20 additionally includes a number ofroutines depicted generally with the numeral 22 for the processing ofdata. The routines 22 can be in any of a variety of forms such as,without limitation, software, firmware, and the like. As will beexplained in greater detail below, the routines 22 include theaforementioned disambiguation function as an application, as well asother routines.

As can be understood from FIG. 2A, the memory 20 additionally includesdata stored and/or organized in a number of tables, sets, lists, and/orotherwise. Specifically, the memory 20 includes a generic word list 88,a new words database 92, and a number of other data sources 99. Whileonly a single other data source 99 is depicted in FIG. 2A, it isunderstood that any quantity of other data sources 99 may be providedand used.

Stored within the various areas of the memory 20 are a number oflanguage objects 100 and frequency objects 104. The language objects 100generally are each associated with an associated frequency object 104.The language objects 100 include, in the present exemplary embodiment, aplurality of word objects 108 and a plurality of N-gram objects 112. Theword objects 108 are generally representative of complete words withinthe language or custom words stored in the memory 20. For instance, ifthe language stored in the memory 20 is, for example, English, generallyeach word object 108 would represent a word in the English language orwould represent a custom word.

Associated with substantially each word object 108 is a frequency object104 having a frequency value that is indicative of the relativefrequency within the relevant language of the given word represented bythe word object 108. In this regard, the generic word list 88 includes aplurality of word objects 108 and associated frequency objects 104 thattogether are representative of a wide variety of words and theirrelative frequency within a given vernacular of, for instance, a givenlanguage. The generic word list 88 can be derived in any of a widevariety of fashions, such as by analyzing numerous texts and otherlanguage sources to determine the various words within the languagesources as well as their relative probabilities, i.e., relativefrequencies, of occurrences of the various words within the languagesources.

The N-gram objects 112 stored within the generic word list 88 are shortstrings of characters within the relevant language typically, forexample, one to three characters in length, and typically represent wordfragments within the relevant language, although certain of the N-gramobjects 112 additionally can themselves be words. However, to the extentthat an N-gram object 112 also is a word within the relevant language,the same word likely would be separately stored as a word object 108within the generic word list 88. As employed herein, the expression“string” and variations thereof shall refer broadly to an object havingone or more characters or components, and can refer to any of a completeword, a fragment of a word, a custom word or expression, and the like.

In the present exemplary embodiment of the handheld electronic device 4,the N-gram objects 112 include 1-gram objects, i.e., string objects thatare one character in length, 2-gram objects, i.e., string objects thatare two characters in length, and 3-gram objects, i.e., string objectsthat are three characters in length, all of which are collectivelyreferred to as N-gram objects 112. Substantially each N-gram object 112in the generic word list 88 is similarly associated with an associatedfrequency object 104 stored within the generic word list 88, but thefrequency object 104 associated with a given N-gram object 112 has afrequency value that indicates the relative probability that thecharacter string represented by the particular N-gram object 112 existsat any location within any word of the relevant language. The N-gramobjects 112 and the associated frequency objects 104 are a part of thecorpus of the generic word list 88 and are obtained in a fashion similarto the way in which the word object 108 and the associated frequencyobjects 104 are obtained, although the analysis performed in obtainingthe N-gram objects 112 will be slightly different because it willinvolve analysis of the various character strings within the variouswords instead of relying primarily on the relative occurrence of a givenword.

The present exemplary embodiment of the handheld electronic device 4,with its exemplary language being the English language, includestwenty-six 1-gram N-gram objects 112, i.e., one 1-gram object for eachof the twenty-six letters in the Latin alphabet upon which the Englishlanguage is based, and further includes 676 2-gram N-gram objects 112,i.e., twenty-six squared, representing each two-letter permutation ofthe twenty-six letters within the Latin alphabet.

The N-gram objects 112 also include a certain quantity of 3-gram N-gramobjects 112, primarily those that have a relatively high frequencywithin the relevant language. The exemplary embodiment of the handheldelectronic device 4 includes fewer than all of the three-letterpermutations of the twenty-six letters of the Latin alphabet due toconsiderations of data storage size, and also because the 2-gram N-gramobjects 112 can already provide a meaningful amount of informationregarding the relevant language. As will be set forth in greater detailbelow, the N-gram objects 112 and their associated frequency objects 104provide frequency data that can be attributed to character strings forwhich a corresponding word object 108 cannot be identified or has notbeen identified, and typically is employed as a fallback data source,although this need not be exclusively the case.

In the present exemplary embodiment, the language objects 100 and thefrequency objects 104 are maintained substantially inviolate in thegeneric word list 88, meaning that the basic language dictionary remainssubstantially unaltered within the generic word list 88, and thelearning functions that are provided by the handheld electronic device 4and that are described below operate in conjunction with other objectsthat are generally stored elsewhere in memory 20, such as, for example,in the new words database 92.

The new words database 92 stores additional word objects 108 andassociated frequency objects 104 in order to provide to a user acustomized experience in which words and the like that are usedrelatively more frequently by a user will be associated with relativelyhigher frequency values than might otherwise be reflected in the genericword list 88. More particularly, the new words database 92 includes wordobjects 108 that are user-defined and that generally are not found amongthe word objects 108 of the generic word list 88. Each word object 108in the new words database 92 has associated therewith an associatedfrequency object 104 that is also stored in the new words database 92.

FIGS. 3A, 3B, and 3C depict in an exemplary fashion the generaloperation of certain aspects of the disambiguation function of thehandheld electronic device 4. Additional features, functions, and thelike are depicted and described elsewhere.

An input is detected, as at 204, and the input can be any type ofactuation or other operation as to any portion of the input apparatus 8.A typical input would include, for instance, an actuation of a key 28having a number of characters 48 thereon, or any other type of actuationor manipulation of the input apparatus 8.

The disambiguation function then determines, as at 212, whether thecurrent input is an operational input, such as a selection input, adelimiter input, a movement input, an alternation input, or, forinstance, any other input that does not constitute an actuation of a key28 having a number of characters 48 thereon. If the input is determinedat 212 to not be an operational input, processing continues at 214 whereit is determined whether or not the input is a part of an editing inputwith respect to a portion of text, such as a word or number ofcharacters that have been output on the display 60. If it is determinedthat the input is an editing input, processing continues to 316 in FIG.3C. However, if it is determined that the input is not editing input,processing continues at 216 by adding the input to the current inputsequence which may or may not already include an input.

Many of the inputs detected at 204 are employed in generating inputsequences as to which the disambiguation function will be executed. Aninput sequence is built up in each “session” with each actuation of akey 28 having a number of characters 48 thereon. Since an input sequencetypically will be made up of at least one actuation of a key 28 having aplurality of characters 48 thereon, the input sequence will beambiguous. When a word, for example, is completed the current session isended an a new session is initiated.

An input sequence is gradually built up on the handheld electronicdevice 4 with each successive actuation of a key 28 during any givensession. Specifically, once a delimiter input is detected during anygiven session, the session is terminated and a new session is initiated.Each input resulting from an actuation of one of the keys 28 having anumber of the characters 48 associated therewith is sequentially addedto the current input sequence. As the input sequence grows during agiven session, the disambiguation function generally is executed witheach actuation of a key 28, i.e., input, and as to the entire inputsequence. Stated otherwise, within a given session, the growing inputsequence is attempted to be disambiguated as a unit by thedisambiguation function with each successive actuation of the variouskeys 28.

Once a current input representing a most recent actuation of the one ofthe keys 28 having a number of the characters 48 assigned thereto hasbeen added to the current input sequence within the current session, asat 216 in FIG. 3A, the disambiguation function generates, as at 220,substantially all of the permutations of the characters 48 assigned tothe various keys 28 that were actuated in generating the input sequence.In this regard, the “permutations” refer to the various strings that canresult from the characters 48 of each actuated key 28 limited by theorder in which the keys 28 were actuated. The various permutations ofthe characters in the input sequence are employed as prefix objects.

For instance, if the current input sequence within the current sessionis the ambiguous input of the keys “AS” and “OP”, the variouspermutations of the first character 52 and the second character 56 ofeach of the two keys 28, when considered in the sequence in which thekeys 28 were actuated, would be “SO”, “SP”, “AP”, and “AO”, and each ofthese is a prefix object that is generated, as at 220, with respect tothe current input sequence. As will be explained in greater detailbelow, the disambiguation function seeks to identify for each prefixobject one of the word objects 108 for which the prefix object would bea prefix.

For each generated prefix object, the memory 20 is consulted, as at 224,to identify, if possible, for each prefix object one of the word objects108 in the memory 20 that corresponds with the prefix object, meaningthat the sequence of letters represented by the prefix object would beeither a prefix of the identified word object 108 or would besubstantially identical to the entirety of the word object 108. Furtherin this regard, the word object 108 that is sought to be identified isthe highest frequency word object 108. That is, the disambiguationfunction seeks to identify the word object 108 that corresponds with theprefix object and that also is associated with a frequency object 104having a relatively higher frequency value than any of the otherfrequency objects 104 associated with the other word objects 108 thatcorrespond with the prefix object.

It is noted in this regard that the word objects 108 in the generic wordlist 88 are generally organized in data tables that correspond with thefirst two letters of various words. For instance, the data tableassociated with the prefix “CO” would include all of the words such as“CODE”, “COIN”, “COMMUNICATION”, and the like. Depending upon thequantity of word objects 108 within any given data table, the data tablemay additionally include sub-data tables within which word objects 108are organized by prefixes that are three characters or more in length.Continuing onward with the foregoing example, if the “CO” data tableincluded, for instance, more than 256 word objects 108, the “CO” datatable would additionally include one or more sub-data tables of wordobjects 108 corresponding with the most frequently appearingthree-letter prefixes. By way of example, therefore, the “CO” data tablemay also include a “COM” sub-data table and a “CON” sub-data table. If asub-data table includes more than the predetermined number of wordobjects 108, for example a quantity of 256, the sub-data table mayinclude further sub-data tables, such as might be organized according toa-four-letter prefixes. It is noted that the aforementioned quantity of256 of the word objects 108 corresponds with the greatest numericalvalue that can be stored within one byte of the memory 20.

Accordingly, when, at 224, each prefix object is sought to be used toidentify a corresponding word object 108, and for instance the instantprefix object is “AP”, the “AP” data table will be consulted. Since allof the word objects 108 in the “AP” data table will correspond with theprefix object “AP”, the word object 108 in the “AP” data table withwhich is associated a frequency object 104 having a frequency valuerelatively higher than any of the other frequency objects 104 in the“AP” data table is identified. The identified word object 108 and theassociated frequency object 104 are then stored in a result registerthat serves as a result of the various comparisons of the generatedprefix objects with the contents of the memory 20.

It is noted that one or more, or possibly all, of the prefix objectswill be prefix objects for which a corresponding word object 108 is notidentified in the memory 20. Such prefix objects are considered to beorphan prefix objects and are separately stored or are otherwiseretained for possible future use. In this regard, it is noted that manyor all of the prefix objects can become orphan objects if, for instance,the user is trying to enter a new word or, for example, if the user hasmis-keyed and no word corresponds with the mis-keyed input.

Processing continues, as at 232, where duplicate word objects 108associated with relatively lower frequency values are deleted from theresult. Such a duplicate word object 108 could be generated, forinstance, by the other data source 99.

Once the duplicate word objects 108 and the associated frequency objects104 have been removed at 232, processing continues to 236 wherein theremaining prefix objects are arranged in an output set in decreasingorder of frequency value.

If it is determined, as at 240, that the flag has been set, meaning thata user has made a selection input, either through an express selectioninput or through an alternation input of a movement input, then thedefault output 76 is considered to be “locked,” meaning that theselected variant will be the default prefix until the end of thesession. If it is determined at 240 that the flag has been set, theprocessing will proceed to 244 where the contents of the output set willbe altered, if needed, to provide as the default output 76 an outputthat includes the selected prefix object, whether it corresponds with aword object 108 or is an artificial variant. In this regard, it isunderstood that the flag can be set additional times during a session,in which case the selected prefix associated with resetting of the flagthereafter becomes the “locked” default output 76 until the end of thesession or until another selection input is detected.

Processing then continues, as at 248, to an output step after which anoutput 64 is generated as described above. Processing thereaftercontinues at 204 where additional input is detected. On the other hand,if it is determined at 240 that the flag has not been set, thenprocessing goes directly to 248 without the alteration of the contentsof the output set at 244.

If at 214 it was determined that the input was a part of an editinginput, such as might occur during an editing operation on an existingword or on a number of characters that are already output on thedisplay, the disambiguation routine 22 advantageously performs aplurality of disambiguation analyses. This most particularly occurs ifan editing input is detected at a location preceding one or morecharacters that have already been displayed. In the exemplary embodimentdepicted herein, the language being employed is the English language,which reads in a left-to-right direction, and thus the word “preceding”would refer to being to the left of existing characters. It isunderstood, however, that in a language that reads in a right-to-leftdirection, for instance, the expression “preceding” would refer to beingto the right of existing characters, and it is further understood thatin a language that reads in a top-to-bottom direction, for instance, theexpression “preceding” would refer to being above existing characters.

The disambiguation routine 22 will perform a first disambiguationanalysis on the editing input itself, which may comprise one or moreinput member actuations. The disambiguation routine 22 will also performa second disambiguation analysis on the editing input in combinationwith the existing word or number of characters that have already, i.e.,previously, been displayed. The results of the two disambiguationoperations are combined in a single list and are output in order ofdecreasing frequency value. In essence, the disambiguation routine 22recognizes that the additional input member actuations, being at alocation directly preceding one or more other characters, might be apart of a new separate word that is being inserted in front of theexisting word or number of characters, or the additional input memberactuations might be intended to be a number of additional characterspreceding the pre-existing characters and which might result in theformation of a larger word comprising the pre-existing characters.

Such an operation is described in relation to the portion of theflowchart depicted generally in FIG. 3C, and an example is depictedgenerally in FIGS. 9-10. Regarding the brief example, it is noted thatFIG. 9 depicts the word “END” having already been output on the display60, and the caret 84 having been moved to a position immediatelypreceding the word “END”. If a user then actuated the input members<DF><ER><UI> as an ambiguous editing input, the disambiguation routine22 would perform a disambiguation operation on the ambiguous editinginput itself, i.e., the input member actuations <DF><ER><UI> without theadditional characters “END”. That is, the first prefix objects DEI, DEU,DRI, DRU, FEI, FEU, FRI, and FRU would be created from the editing input<DF><ER><UI>, and language objects 100 corresponding with each of theprefix objects would be sought. For instance, the language object 100for “drip” might be identified as corresponding with the prefix object“DRI”, and the language object 100 for “drum” might be identified ascorresponding with the prefix object “DRU”. Other such language objects100 likely will be identified as corresponding with these and the otherprefix objects. Frequency values from the identified language objects100 would be associated with the various first prefix objects DEI, DEU,DRI, DRU, FEI, FEU, FRI, and FRU.

The disambiguation routine 22 would also perform a disambiguationoperation on the ambiguous editing input in combination with theexisting characters “END”. That is, the various character permutationsfrom the input member actuations <DF><ER><UI> in combination with theexisting characters “END” would be created. Thus, the second prefixobjects would be DEIEND, DEUEND, DRIEND, DRUEND, FEIEND, FEUEND, FRIEND,and FRUEND, for example. For each such second prefix object, thedisambiguation routine 22 would seek language objects 100 thatcorrespond with the prefix object. For the example given, if it isassumed that the relevant language is the English language, likely theonly prefix object for which a corresponding word object 108 would befound would be the language object 100 for the complete word “FRIEND”.It is possible that N-gram objects 112 could be identified in order toassociate a frequency value with the other prefix objects, although thefrequency values associated with such prefix objects would besubstantially less than the frequency value associated with the prefixobject “FRIEND”. In any event, frequency values, as appropriate, wouldbe associated with the various second prefix objects DEIEND, DEUEND,DRIEND, DRUEND, FEIEND, FEUEND, FRIEND, and FRUEND.

Since the preexisting output characters “END” are considered in thecurrent editing analysis to be committed, i.e., locked, the characters“END” are appended to each of the first prefix objects generated fromthe editing input. That is, the first prefix objects DEI DEU, DRI, DRU,FEI, FEU, FRI, and FRU, which were mentioned above in connection withthe first of the two exemplary disambiguation operations beingdescribed, and with which frequency values were associated, would become“appended” first prefix objects, thus DEIEND, DEUEND, DRIEND, DRUEND,FEIEND, FEUEND, FRIEND, and FRUEND.

The frequency values associated with the second prefix objects DEIEND,DEUEND, DRIEND, DRUEND, FEIEND, FEUEND, FRIEND, and FRUEND and thefrequency values of the “appended” first prefix objects DEIEND, DEUEND,DRIEND, DRUEND, FEIEND, FEUEND, FRIEND, and FRUEND would then becompared, and the prefix objects arranged in an output set in order ofdecreasing frequency value. Lesser frequency value duplicate prefixobjects would be removed.

For instance, and as can be seen from FIG. 3C, the current input wouldbe added to the editing input sequence at 316. In the present example,if the input <UI> would be added to the existing editing input sequenceto create the current editing input <DF><ER><UI>. Prefix objects for theediting input would be generated at 320 which, in the present example,would be the first prefix objects DEI, DEU, DRI, DRU, FEI, FEU, FRI, andFRU. At 324, language objects 100 would be sought for correspondencewith each first prefix object. Any duplicate language objects 100 withrelatively lower frequency values would be filtered at 332.

At 334, the locked characters “END” would be appended to each of thefirst prefix objects DEI, DEU, DRI, DRU, FEI, FEU, FRI, and FRU, thusforming the “appended” first prefix objects DEIEND, DEUEND, DRIEND,DRUEND, FEIEND, FEUEND, FRIEND, and FRUEND. Appending of the characters“END” that follow these prefix objects to form the “appended” firstprefixes enables these first prefix objects to be compared with theprefix objects that will be generated in a second disambiguationoperation, as will be set forth in greater detail below.

Specifically, the second disambiguation operation would commence at 416.For instance, the current input would be added to the editing inputsequence at 416 and to the pre-existing word “END”. In the presentexample, if the input <UI> would be added to the existing editing inputsequence to create the current editing input <DF><ER><UI>, and would becombined with the characters “END”. Second prefix objects for theediting input in combination with the pre-existing characters “END”would be generated at 420 which, in the present example, would be thesecond prefix objects DEIEND, DEUEND, DRIEND, DRUEND, FEIEND, FEUEND,FRIEND, and FRUEND. At 424, language objects 100 would be sought forcorrespondence with each such second prefix object. In the examplepresented herein, the only word object 108 found as corresponding withany of the second prefix objects would be the word object 108 for thecomplete word “FRIEND”. Any duplicate language objects 100 withrelatively lower frequency values would be filtered at 432.

The “appended” first prefix objects DEIEND, DEUEND, DRIEND, DRUEND,FEIEND, FEUEND, FRIEND, and FRUEND, with associated frequency values,and the second prefix objects DEIEND, DEUEND, DRIEND, DRUEND, FEIEND,FEUEND, FRIEND, and FRUEND, with associated frequency values, would bearranged at 436 in an output list in order of decreasing frequencyvalue. Lesser-frequency duplicate prefix objects would then be removedat 438.

In this regard, it is noted that by appending “END” to the first prefixobjects to form the “appended” first prefix objects, the “appended”first prefix objects DEIEND, DEUEND, DRIEND, DRUEND, FEIEND, FEUEND,FRIEND, and FRUEND, are the same as the second prefix objects DEIEND,DEUEND, DRIEND, DRUEND, FEIEND, FEUEND, FRIEND, and FRUEND. However, itis noted that the frequency values associated with the appended firstprefix objects are those that were obtained by performing adisambiguation analysis on the first prefix objects DEL DEU, DRI, DRU,FEI, FEU, FRI, and FRU, whereas the frequency values associated with thesecond prefix objects were obtained from performing the disambiguationanalysis on the second prefix objects DEIEND, DEUEND, DRIEND, DRUEND,FEIEND, FEUEND, FRIEND, and FRUEND. Transforming the first prefixobjects into “appended” first prefix objects enables lower-frequencyduplicate appended first prefix objects and/or second prefix objects tobe removed from the output list. It also enables, as set forth below,the outputting of variants that are all of the same length. Thisadvantageously enables the user to receive the best possibledisambiguation analysis with respect to the text being edited.

If it is determined, as at 440, that the flag has been set, then thedefault output 76 is considered to be “locked,” in a fashion similar tothat set forth above at 240, and processing will proceed to 444 wherethe contents of the output set will be altered, if needed. Processingthen continues, as at 448, to an output step after which an output 64 isgenerated as described above. Processing thereafter continues at 204where additional input is detected. On the other hand, if it isdetermined at 440 that the flag had not been set, then processing goesdirectly to 448 without the alteration of the contents of the output setat 444.

It is noted that if either a first or a second prefix object isidentified as being a complete word, such prefix object is output as thedefault output. If, for instance, both a first prefix object and asecond prefix object are identified as being complete words, the two areoutput at the top of the selection list, with the one having the higherfrequency value associated therewith being output as the default, andwith the other being the first variant output. Such a complete wordprefix object will, if necessary, be output with any pre-existingtrailing characters being appended.

It is also noted that any characters preceding the editing input areconsidered to be locked and considered to be a part of the editinginput. For instance, if instead of the word “END” being the pre-existingword, the preexisting word was “SEND”, and the caret 84 provided theediting input immediately preceding the “E” and immediately followingthe “S” in “SEND”. The first prefix objects would be SDEI, SDEU, SDRI,SDRU, SFEI, SFEU, SFRI, and SFRU, and corresponding language objects 100would be sought. The “appended” first prefix objects would be SDEIEND,SDEUEND, SDRIEND, SDRUEND, SFEIEND, SFEUEND, SFRIEND, and SFRUEND, withthe END portion being appended after language objects 100 wereidentified and frequency values associated with the first prefixobjects. The second prefix objects would be SDEIEND, SDEUEND, SDRIEND,SDRUEND, SFEIEND SFEUEND, SFRIEND, and SFRUEND, and correspondinglanguage objects 100 would be sought for each.

If the detected input is determined, as at 212, to be an operationalinput, processing then continues to determine the specific nature of theoperational input. For instance, if it is determined, as at 252, thatthe current input is a selection input, processing continues at 254where the flag is set. Processing then returns to detection ofadditional inputs as at 204.

If it is determined, as at 260, that the input is a delimiter input,processing continues at 264 where the current session is terminated andprocessing is transferred, as at 266, to the learning functionsubsystem, as at 404 of FIG. 4. A delimiter input would include, forexample, the actuation of a <SPACE> key 116, which would both enter adelimiter symbol and would add a space at the end of the word, actuationof the <ENTER> key, which might similarly enter a delimiter input andenter a space, and by a translation of the thumbwheel 32, such as isindicated by the arrow 38, which might enter a delimiter input withoutadditionally entering a space.

It is first determined, as at 408, whether the default output at thetime of the detection of the delimiter input at 260 matches a wordobject 108 in the memory 20. If it does not, this means that the defaultoutput is a user-created output that should be added to the new wordsdatabase 92 for future use. In such a circumstance processing thenproceeds to 412 where the default output is stored in the new wordsdatabase 92 as a new word object 108. Additionally, a frequency object104 is stored in the new words database 92 and is associated with theaforementioned new word object 108. The new frequency object 104 isgiven a relatively high frequency value, typically within the upperone-fourth or one-third of a predetermined range of possible frequencyvalues.

In this regard, frequency objects 104 are given an absolute frequencyvalue generally in the range of zero to 65,535. The maximum valuerepresents the largest number that can be stored within two bytes of thememory 20. The new frequency object 104 that is stored in the new wordsdatabase 92 is assigned an absolute frequency value within the upperone-fourth or one-third of this range, particularly since the new wordwas used by a user and is likely to be used again.

With further regard to frequency object 104, it is noted that within agiven data table, such as the “CO” data table mentioned above, theabsolute frequency value is stored only for the frequency object 104having the highest frequency value within the data table. All of theother frequency objects 104 in the same data table have frequency valuesstored as percentage values normalized to the aforementioned maximumabsolute frequency value. That is, after identification of the frequencyobject 104 having the highest frequency value within a given data table,all of the other frequency objects 104 in the same data table areassigned a percentage of the absolute maximum value, which representsthe ratio of the relatively smaller absolute frequency value of aparticular frequency object 104 to the absolute frequency value of theaforementioned highest value frequency object 104. Advantageously, suchpercentage values can be stored within a single byte of memory, thussaving storage space within the handheld electronic device 4.

Upon creation of the new word object 108 and the new frequency object104, and storage thereof within the new words database 92, processing istransferred to 420 where the learning process is terminated. Processingis then returned to the main process, as at 204. If at 408 it isdetermined that the word object 108 in the default output 76 matches aword object 108 within the memory 20, processing is returned directly tothe main process at 204.

With further regard to the identification of various word objects 108for correspondence with generated prefix objects, it is noted that thememory 20 can include a number of additional data sources 99 in additionto the generic word list 88 and the new words database 92, all of whichcan be considered linguistic sources. It is understood that the memory20 might include any number of other data sources 99. The other datasources 99 might include, for example, an address database, a speed-textdatabase, or any other data source without limitation. An exemplaryspeed-text database might include, for example, sets of words orexpressions or other data that are each associated with, for example, acharacter string that may be abbreviated. For example, a speed-textdatabase might associate the string “br” with the set of words “BestRegards”, with the intention that a user can type the string “br” andreceive the output “Best Regards”.

In seeking to identify word objects 108 that correspond with a givenprefix object, the handheld electronic device 4 may poll all of the datasources in the memory 20. For instance the handheld electronic device 4may poll the generic word list 88, the new words database 92, and theother data sources 99 to identify word objects 108 that correspond withthe prefix object. The contents of the other data sources 99 may betreated as word objects 108, and the processor 16 may generate frequencyobjects 104 that will be associated with such word objects 108 and towhich may be assigned a frequency value in, for example, the upperone-third or one-fourth of the aforementioned frequency range. Assumingthat the assigned frequency value is sufficiently high, the string “br”,for example, would typically be output to the display 60. If a delimiterinput is detected with respect to the portion of the output having theassociation with the word object 108 in the speed-text database, forinstance “br”, the user would receive the output “Best Regards”, itbeing understood that the user might also have entered a selection inputas to the exemplary string “br”.

The contents of any of the other data sources 99 may be treated as wordobjects 108 and may be associated with generated frequency objects 104having the assigned frequency value in the aforementioned upper portionof the frequency range. After such word objects 108 are identified, thenew word learning function can, if appropriate, act upon such wordobjects 108 in the fashion set forth above.

If it is determined, such as at 268, that the current input is amovement input, such as would be employed when a user is seeking to editan object, either a completed word or a prefix object within the currentsession, the caret 84 is moved, as at 272, to the desired location, andthe flag is set, as at 276. Processing then returns to where additionalinputs can be detected, as at 204.

In this regard, it is understood that various types of movement inputscan be detected from the input apparatus 8. For instance, a rotation ofthe thumbwheel 32, such as is indicated by the arrow 34 of FIG. 1, couldprovide a movement input. In the instance where such a movement input isdetected, such as in the circumstance of an editing input, the movementinput is additionally detected as a selection input. Accordingly, and asis the case with a selection input such as is detected at 252, theselected variant is effectively locked with respect to the defaultportion 76 of the output 64. Any default output 76 during the samesession will necessarily include the previously selected variant.

In the present exemplary embodiment of the handheld electronic device 4,if it is determined, as at 252, that the input is not a selection input,and it is determined, as at 260, that the input is not a delimiterinput, and it is further determined, as at 268, that the input is not amovement input, in the current exemplary embodiment of the handheldelectronic device 4 the only remaining operational input generally is adetection of the <DELETE> key 86 of the keys 28 of the keypad 24. Upondetection of the <DELETE> key 86, the final character of the defaultoutput is deleted, as at 280. Processing thereafter returns to 204 whereadditional input can be detected.

An exemplary input sequence is depicted in FIGS. 1 and 5-8. In thisexample, the user is attempting to enter the word “APPLOADER”, and thisword presently is not stored in the memory 20. In FIG. 1 the user hasalready typed the “AS” key 28. Since the data tables in the memory 20are organized according to two-letter prefixes, the contents of theoutput 64 upon the first keystroke are obtained from the N-gram objects112 within the memory 20. The first keystroke “AS” corresponds with afirst N-gram object 112 “S” and an associated frequency object 104, aswell as another N-gram object 112 “A” and associated frequency object104. While the frequency object 104 associated with “S” has a frequencyvalue greater than that of the frequency object 104 associated with “A”,it is noted that “A” is itself a complete word. A complete word isalways provided as the default output 76 in favor of other prefixobjects that do not match complete words, regardless of associatedfrequency value. As such, in FIG. 1, the default portion 76 of theoutput 64 is “A”.

In FIG. 5, the user has additionally entered the “OP” key 28. Thevariants are depicted in FIG. 5. Since the prefix object “SO” is also aword, it is provided as the default output 76. In FIG. 6, the user hasagain entered the “OP” key 28 and has also entered the “L” key 28. It isnoted that the exemplary “L” key 28 depicted herein includes only thesingle character 48 “L”.

It is assumed in the instant example that no operational inputs havethus far been detected. The default output 76 is “APPL”, such as wouldcorrespond with the word “APPLE”. The prefix “APPL” is depicted both inthe text component 68, as well as in the default portion 76 of thevariant component 72. Variant prefix objects in the variant portion 80include “APOL”, such as would correspond with the word “APOLOGIZE”, andthe prefix “SPOL”, such as would correspond with the word “SPOLIATION”.

It is particularly noted that the additional variants “AOOL”, “AOPL”,“SOPL”, and “SOOL” are also depicted as variants 80 in the variantcomponent 72. Since no word object 108 corresponds with these prefixobjects, the prefix objects are considered to be orphan prefix objectsfor which a corresponding word object 108 was not identified. In thisregard, it may be desirable for the variant component 72 to include aspecific quantity of entries, and in the case of the instant exemplaryembodiment the quantity is seven entries. Upon obtaining the result at224, if the quantity of prefix objects in the result is fewer than thepredetermined quantity, the disambiguation function will seek to provideadditional outputs until the predetermined number of outputs areprovided.

In FIG. 7 the user has additionally entered the “OP” key 28. In thiscircumstance, and as can be seen in FIG. 7, the default portion 76 ofthe output 64 has become the prefix object “APOLO” such as wouldcorrespond with the word “APOLOGIZE”, whereas immediately prior to thecurrent input the default portion 76 of the output 64 of FIG. 6 was“APPL” such as would correspond with the word “APPLE.” Again, assumingthat no operational inputs had been detected, the default prefix objectin FIG. 7 does not correspond with the previous default prefix object ofFIG. 6. As such, a first artificial variant “APOLP” is generated and inthe current example is given a preferred position. The aforementionedartificial variant “APOLP” is generated by deleting the final characterof the default prefix object “APOLO” and by supplying in its place anopposite character 48 of the key 28 which generated the final characterof the default portion 76 of the output 64, which in the current exampleof FIG. 7 is “P”, so that the aforementioned artificial variant is“APOLP”.

Furthermore, since the previous default output “APPL” corresponded witha word object 108, such as the word object 108 corresponding with theword “APPLE”, and since with the addition of the current input theprevious default output “APPL” no longer corresponds with a word object108, two additional artificial variants are generated. One artificialvariant is “APPLP” and the other artificial variant is “APPLO”, andthese correspond with the previous default output “APPL” plus thecharacters 48 of the key 28 that was actuated to generate the currentinput. These artificial variants are similarly output as part of thevariant portion 80 of the output 64.

As can be seen in FIG. 7, the default portion 76 of the output 64“APOLO” no longer seems to match what would be needed as a prefix for“APPLOADER”, and the user likely anticipates that the desired word“APPLOADER” is not already stored in the memory 20. As such, the userprovides a selection input, such as by scrolling with the thumbwheel 32until the variant string “APPLO” is highlighted. The user then continuestyping and enters the “AS” key.

The output 64 of such action is depicted in FIG. 8. Here, the string“APPLOA” is the default portion 76 of the output 64. Since the variantstring “APPLO” became the default portion 76 of the output 64 (notexpressly depicted herein) as a result of the selection input as to thevariant string “APPLO”, and since the variant string “APPLO” does notcorrespond with a word object 108, the character strings “APPLOA” and“APPLOS” were created as artificial variants. Additionally, since theprevious default of FIG. 7, “APOLO” previously had corresponded with aword object 108, but now is no longer in correspondence with the defaultportion 76 of the output 64 of FIG. 8, the additional artificialvariants of “APOLOA” and “APOLOS” were also generated. Such artificialvariants are given a preferred position in favor of the three displayedorphan prefix objects.

Since the current input sequence in the example no longer correspondswith any word object 108, the portions of the method related toattempting to find corresponding word objects 108 are not executed withfurther inputs for the current session. That is, since no word object108 corresponds with the current input sequence, her inputs willlikewise not correspond with any word object 108. Avoiding the search ofthe memory 20 for such nonexistent word objects 108 saves time andavoids wasted processing effort.

As the user continues to type, the user ultimately will successfullyenter the word “APPLOADER” and will enter a delimiter input. Upondetection of the delimiter input after the entry of “APPLOADER”, thelearning function is initiated. Since the word “APPLOADER” does notcorrespond with a word object 108 in the memory 20, a new word object108 corresponding with “APPLOADER” is generated and is stored in the newwords database 92, along with a corresponding new frequency object 104which is given an absolute frequency in the upper, say, one-third orone-fourth of the possible frequency range. In this regard, it is notedthat the new words database 92 is generally organized in two-characterprefix data tables similar to those found in the generic word list 88.As such, the new frequency object 104 is initially assigned an absolutefrequency value, but upon storage, the absolute frequency value, if itis not the maximum value within that data table, will be changed toinclude a normalized frequency value percentage normalized to whateveris the maximum frequency value within that data table.

It is noted that the layout of the characters 48 disposed on the keys 28in FIG. 1 is an exemplary character layout that would be employed wherethe intended primary language used on the handheld electronic device 4was, for instance, English. Other layouts involving these characters 48and/or other characters can be used depending upon the intended primarylanguage and any language bias in the makeup of the language objects100.

As mentioned elsewhere herein, a complete word that is identified duringa disambiguation cycle is always provided as a default output 76 infavor of other prefix objects that do not match complete words,regardless of associated frequency value. That is, a word object 108corresponding with an ambiguous input and having a length equal to thatof the ambiguous input is output at a position of priority over otherprefix objects. As employed herein, the expression “length” andvariations thereof shall refer broadly to a quantity of elements ofwhich an object is comprised, such as the quantity of linguisticelements of which a language object 100 is comprised.

If more than one complete word is identified during a disambiguationcycle, all of the complete words may be output in order of decreasingfrequency with respect to one another, with each being at a position ofpriority over the prefix objects that are representative of incompletewords. However, it may be desirable in certain circumstances to employadditional data, if available, to prioritize the complete words in a waymore advantageous to the user.

While specific embodiments of the disclosed and claimed concept havebeen described in detail, it will be appreciated by those skilled in theart that various modifications and alternatives to those details couldbe developed in light of the overall teachings of the disclosure.Accordingly, the particular arrangements disclosed are meant to beillustrative only and not limiting as to the scope of the disclosed andclaimed concept which is to be given the full breadth of the claimsappended and any and all equivalents thereof.

1. A method of enabling input into a handheld electronic device of atype comprising an input apparatus, an output apparatus, and a processorapparatus that comprises a memory having stored therein a plurality ofobjects including a number of language objects, the input apparatusincluding a plurality of input members, at least some of the inputmembers each having a plurality of linguistic elements assigned thereto,the method comprising: providing, by the handheld electronic device, asa first output a number of linguistic elements; detecting as anambiguous editing input a number of input member actuations at alocation that precedes at least a portion of the first output; employinga number of first language objects that each correspond with at least aportion of the editing input to generate a number of first linguisticresults; employing a number of second language objects that eachcorrespond with at least a portion of the editing input in combinationwith at least some of the linguistic elements of the at least a portionof the first output to generate a number of second linguistic results;and outputting at least one of: at least some of the first linguisticresults, and at least some of the second linguistic results.
 2. Themethod of claim 1, wherein the plurality of objects further comprise aplurality of frequency objects, at least some of the frequency objectseach having a frequency value, at least some of the language objectseach having a frequency object associated therewith, the method furthercomprising outputting the at least one of: at least some of the firstlinguistic results, and at least some of the second linguistic resultsin order of decreasing frequency value.
 3. The method of claim 2,further comprising comparing a first frequency value of at least one ofthe first linguistic results with a second frequency value of at leastone of the second linguistic results.
 4. The method of claim 1, furthercomprising: employing, as the first language objects, a number oflanguage objects that each correspond with at least a portion of theediting input in combination with at least some of the linguisticelements of a portion of the first output that precedes the number ofinput member actuations; and employing, as the second language objects,a number of language objects that each correspond with at least aportion of the editing input in combination with at least some of thelinguistic elements of the at least a portion of the first output, andfurther in combination with at least some of the linguistic elements ofa portion of the first output that precedes the number of input memberactuations.
 5. The method of claim 1, further comprising outputting, asthe at least some of the first linguistic results, at least some of thefirst linguistic results each having appended thereto at least some ofthe linguistic elements of the at least a portion of the first output.6. A handheld electronic device comprising: an input apparatuscomprising a plurality of input members, at least some of the inputmembers each having a plurality of linguistic elements assigned thereto;an output apparatus; and a processor apparatus that comprises aprocessor and a memory having stored therein a plurality of objectsincluding a number of language objects, the memory further having storedtherein a number of routines which, when executed on the processor,cause the handheld electronic device to perform operations comprising:providing as a first output a number of linguistic elements; detectingas an ambiguous editing input a number of input member actuations at alocation that precedes at least a portion of the first output; employinga number of first language objects that each correspond with at least aportion of the editing input to generate a number of first linguisticresults; employing a number of second language objects that eachcorrespond with at least a portion of the editing input in combinationwith at least some of the linguistic elements of the at least a portionof the first output to generate a number of second linguistic results;and outputting at least one of: at least some of the first linguisticresults, and at least some of the second linguistic results.
 7. Thehandheld electronic device of claim 6, wherein the plurality of objectsfurther comprise a plurality of frequency objects, at least some of thefrequency objects each having a frequency value, at least some of thelanguage objects each having a frequency object associated therewith,and wherein the operations further comprise outputting the at least oneof: at least some of the first linguistic results, and at least some ofthe second linguistic results in order of decreasing frequency value. 8.The handheld electronic device of claim 7, wherein the operationsfurther comprise comparing a first frequency value of at least one ofthe first linguistic results with a second frequency value of at leastone of the second linguistic results.
 9. The handheld electronic deviceof claim 6, wherein the operations further comprise outputting, as theat least some of the first linguistic results, at least some of thefirst linguistic results each having appended thereto at least some ofthe linguistic elements of the at least a portion of the first output.10. A method of enabling input into a handheld electronic device of atype comprising an input apparatus providing a plurality of linguisticelements, an output apparatus, and a processor apparatus that comprisesa memory having stored therein a plurality of objects including a numberof language objects, the method comprising: providing, by the handheldelectronic device, as a first output a number of linguistic elements;detecting an ambiguous editing input at a location that precedes atleast a portion of the first output; employing a number of firstlanguage objects that each correspond with at least a portion of theediting input to generate a number of first linguistic results;employing a number of second language objects that each correspond withat least a portion of the editing input in combination with at leastsome of the linguistic elements of the at least a portion of the firstoutput to generate a number of second linguistic results; and outputtingat least one of: at least some of the first linguistic results, and atleast some of the second linguistic results.
 11. A handheld electronicdevice comprising: an input apparatus providing a plurality oflinguistic elements; an output apparatus; and a processor apparatus thatcomprises a processor and a memory having stored therein a plurality ofobjects including a number of language objects, the memory furtherhaving stored therein a number of routines which, when executed on theprocessor, cause the handheld electronic device to perform operationscomprising: providing as a first output a number of linguistic elements;detecting an ambiguous editing input at a location that precedes atleast a portion of the first output; employing a number of firstlanguage objects that each correspond with at least a portion of theediting input to generate a number of first linguistic results;employing a number of second language objects that each correspond withat least a portion of the editing input in combination with at leastsome of the linguistic elements of the at least a portion of the firstoutput to generate a number of second linguistic results; and outputtingat least one of: at least some of the first linguistic results, and atleast some of the second linguistic results.